PURPOSE: Accurate tumor classification is essential for cancer management as patient outcomes improve with use of site- and subtype-specific therapies. Current clinicopathologic evaluation is varied in approach, yet standardized diagnoses are critical for determining therapy. While gene expression-based cancer classifiers may potentially meet this need, imperative to determining their application to patient care is validation in rigorously designed studies. Here, we examined the performance of a 92-gene molecular classifier in a large multi-institution cohort. EXPERIMENTAL DESIGN: Case selection incorporated specimens from more than 50 subtypes, including a range of tumor grades, metastatic and primary tumors, and limited tissue samples. Formalin-fixed, paraffin-embedded tumors passed pathologist-adjudicated review between three institutions. Tumor classification using a 92-gene quantitative reverse transcriptase polymerase chain reaction (RT-PCR) assay was conducted on blinded tumor sections from 790 cases and compared with adjudicated diagnoses. RESULTS: The 92-gene assay showed overall sensitivities of 87% for tumor type [95% confidence interval (CI), 84-89] and 82% for subtype (95% CI, 79-85). Analyses of metastatic tumors, high-grade tumors, or cases with limited tissue showed no decrease in comparative performance (P = 0.16, 0.58, and 0.16). High specificity (96%-100%) was showed for ruling in a primary tumor in organs commonly harboring metastases. The assay incorrectly excluded the adjudicated diagnosis in 5% of cases. CONCLUSIONS: The 92-gene assay showed strong performance for accurate molecular classification of a diverse set of tumor histologies. Results support potential use of the assay as a standardized molecular adjunct to routine clinicopathologic evaluation for tumor classification and primary site diagnosis.
PURPOSE: Accurate tumor classification is essential for cancer management as patient outcomes improve with use of site- and subtype-specific therapies. Current clinicopathologic evaluation is varied in approach, yet standardized diagnoses are critical for determining therapy. While gene expression-based cancer classifiers may potentially meet this need, imperative to determining their application to patient care is validation in rigorously designed studies. Here, we examined the performance of a 92-gene molecular classifier in a large multi-institution cohort. EXPERIMENTAL DESIGN: Case selection incorporated specimens from more than 50 subtypes, including a range of tumor grades, metastatic and primary tumors, and limited tissue samples. Formalin-fixed, paraffin-embedded tumors passed pathologist-adjudicated review between three institutions. Tumor classification using a 92-gene quantitative reverse transcriptase polymerase chain reaction (RT-PCR) assay was conducted on blinded tumor sections from 790 cases and compared with adjudicated diagnoses. RESULTS: The 92-gene assay showed overall sensitivities of 87% for tumor type [95% confidence interval (CI), 84-89] and 82% for subtype (95% CI, 79-85). Analyses of metastatic tumors, high-grade tumors, or cases with limited tissue showed no decrease in comparative performance (P = 0.16, 0.58, and 0.16). High specificity (96%-100%) was showed for ruling in a primary tumor in organs commonly harboring metastases. The assay incorrectly excluded the adjudicated diagnosis in 5% of cases. CONCLUSIONS: The 92-gene assay showed strong performance for accurate molecular classification of a diverse set of tumor histologies. Results support potential use of the assay as a standardized molecular adjunct to routine clinicopathologic evaluation for tumor classification and primary site diagnosis.
Authors: Scott K Sherman; Jessica E Maxwell; Jennifer C Carr; Donghong Wang; Andrew M Bellizzi; M Sue O'Dorisio; Thomas M O'Dorisio; James R Howe Journal: Clin Exp Metastasis Date: 2014-09-21 Impact factor: 5.150
Authors: F Losa; G Soler; A Casado; A Estival; I Fernández; S Giménez; F Longo; R Pazo-Cid; J Salgado; M Á Seguí Journal: Clin Transl Oncol Date: 2017-12-11 Impact factor: 3.405
Authors: H H Yoon; N R Foster; J P Meyers; P D Steen; D W Visscher; R Pillai; D M Prow; C M Reynolds; B T Marchello; R B Mowat; B I Mattar; C Erlichman; M P Goetz Journal: Ann Oncol Date: 2015-11-16 Impact factor: 32.976
Authors: Michael J Overman; Harris S Soifer; Aaron Joel Schueneman; Joe Ensor; Volkan Adsay; Burcu Saka; Nastaran Neishaboori; Robert A Wolff; Huamin Wang; Catherine A Schnabel; Gauri Varadhachary Journal: BMC Cancer Date: 2016-08-22 Impact factor: 4.430